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GCP MCP Server

by JayRajGoyal
GitHub
Python
MIT License
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GCP MCP Server

A Model Context Protocol (MCP) server for Google Cloud Platform (GCP) that enables AI assistants to interact with GCP services, particularly focused on log analysis and root cause investigation.

Features

  • Cloud Logging Integration: Query and analyze GCP Cloud Logging data

  • Real-time Log Streaming: Stream logs for immediate analysis

  • Error Pattern Detection: Identify common error patterns and anomalies

  • Multi-Project Support: Work across multiple GCP projects

  • Secure Authentication: Uses GCP service account credentials

  • Root Cause Analysis: Tools to help with quick RC findings

Supported GCP Services

  • Cloud Logging: Query, filter, and analyze logs

  • Cloud Monitoring: Retrieve metrics and alerts (planned)

  • Error Reporting: Access error statistics and details (planned)

  • Cloud Trace: Distributed tracing analysis (planned)

Installation

⚡ Quick Install

git clone https://github.com/JayRajGoyal/gcp-mcp.git cd gcp-mcp ./install.sh

Claude Code Integration (One Command!)

The easiest way to add this MCP server to Claude Code:

# If you have gcloud configured (recommended): claude mcp add gcp-logs -e GOOGLE_APPLICATION_CREDENTIALS=/Users/$USER/.config/gcloud/application_default_credentials.json -- python3.11 -m gcp_mcp.cli --project YOUR_PROJECT_ID

Or with a service account key file:

claude mcp add gcp -- python3.11 -m gcp_mcp.cli --credentials /path/to/your/service-account-key.json

Manual Configuration (Alternative)

Add this to your Claude Code configuration:

{ "mcpServers": { "gcp": { "command": "python3.11", "args": ["-m", "gcp_mcp.cli", "--credentials", "/path/to/your/credentials.json"], "cwd": "/path/to/gcp-mcp" } } }

Prerequisites

  • Python 3.8 or higher

  • GCP project with appropriate APIs enabled

  • Service account with necessary permissions

Manual Setup

  1. Clone the repository:

git clone https://github.com/JayRajGoyal/gcp-mcp.git cd gcp-mcp

  1. Install dependencies:

pip install -r requirements.txt

  1. Run with your credentials:

python -m gcp_mcp.cli --credentials /path/to/your/credentials.json

Usage

Starting the Server

python -m gcp_mcp.server

Available Tools

Log Query

Query GCP Cloud Logging with advanced filters:

query_logs(project_id, filter, limit, time_range)

Log Analysis

Analyze logs for patterns and anomalies:

analyze_logs(project_id, service_name, time_range)

Error Investigation

Find and analyze error patterns:

investigate_errors(project_id, service_name, time_range)

Configuration

Create a config.json file:

{ "default_project": "your-gcp-project-id", "log_retention_days": 30, "max_results": 1000, "excluded_log_names": [ "projects/your-project/logs/cloudaudit.googleapis.com%2Fdata_access" ] }

Authentication

The server supports multiple authentication methods:

  1. Service Account Key File: Set GOOGLE_APPLICATION_CREDENTIALS

  2. Application Default Credentials: For GCE, Cloud Shell, etc.

  3. User Credentials: Via gcloud auth application-default login

Required GCP Permissions

Your service account needs the following IAM roles:

  • roles/logging.viewer - Read access to Cloud Logging

  • roles/monitoring.viewer - Read access to Cloud Monitoring (optional)

  • roles/errorreporting.viewer - Read access to Error Reporting (optional)

Development

Running Tests

pytest tests/

Code Formatting

black gcp_mcp/ isort gcp_mcp/

Type Checking

mypy gcp_mcp/

Contributing

  1. Fork the repository

  2. Create a feature branch

  3. Make your changes

  4. Add tests

  5. Run the test suite

  6. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Security

  • Never commit service account keys to the repository

  • Use environment variables for sensitive configuration

  • Follow GCP security best practices

  • Report security vulnerabilities via email

Support

  • Create an issue for bug reports or feature requests

  • Check existing issues before creating new ones

  • Provide detailed information including logs and configuration

Roadmap

  • Cloud Monitoring integration

  • Error Reporting tools

  • Cloud Trace analysis

  • BigQuery log export support

  • Alerting and notification tools

  • Dashboard generation

  • Cost analysis tools

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Enables AI assistants to interact with Google Cloud Platform services for log analysis and root cause investigation. Provides tools to query Cloud Logging, detect error patterns, and perform real-time log streaming across multiple GCP projects.

  1. Features
    1. Supported GCP Services
      1. Installation
        1. ⚡ Quick Install
        2. Claude Code Integration (One Command!)
        3. Prerequisites
        4. Manual Setup
      2. Usage
        1. Starting the Server
        2. Available Tools
      3. Configuration
        1. Authentication
          1. Required GCP Permissions
            1. Development
              1. Running Tests
              2. Code Formatting
              3. Type Checking
            2. Contributing
              1. License
                1. Security
                  1. Support
                    1. Roadmap

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